Siedrix 🐱

Product builder and tinker. Learning to fly. Eternal Don Quixote.

[Siedrix 🐱 @Siedrix]

https://t.co/1OK2BsGBL0

[Siedrix 🐱 @Siedrix]

Como va el mundo... se antoja...

[David ImeI @DurvidImel]

2026

[Siedrix 🐱 @Siedrix]

Great takes...

[Siedrix 🐱 @Siedrix]

En la empoca de AI, pasaremos del 2 pizza teams... a 2 burritos and a chemex team...

Principalmente por que coordinar a mas gente sera mucho overhead. Mejor mandar a prod y checar que dice data dog y amplitude

[Siedrix 🐱 @Siedrix]

Tal vez dios si existe...

[Siedrix 🐱 @Siedrix]

Karpathy siempre parece del futuro y a la vez diciendo cosas demasiado obvias una vez que las sabes...

Que gran combo...

[Andrej Karpathy @karpathy]

LLM Knowledge Bases

Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So:

Data ingest:
I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them.

IDE:
I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides).

Q&A:
Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale.

Output:
Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base.

Linting:
I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into.

Extra tools:
I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries.

Further explorations:
As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows.

TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

[Siedrix 🐱 @Siedrix]

El presidente en contra de la energía renovable esta causando que la energía renovable sea adoptada... que mundo tan raro vivimos...

[Siedrix 🐱 @Siedrix]

Habran usado Opus4.7 para nombrar el comando /ultrareview y esto es lo que pasa cuando indexas el intenet? o fueron humanos?

Discutan en grupos de 3(LLMs)...

[ClaudeDevs @ClaudeDevs]

New in Claude Code: /ultrareview (research preview) runs a fleet of bug-hunting agents in the cloud.

Findings land in the CLI or Desktop automatically. Run it before merging critical changes—auth, data migrations, etc.

Pro and Max users get 3 free reviews through 5/5.

[Siedrix 🐱 @Siedrix]

Vercel: At this time, we do not have reason to believe that your Vercel credentials or personal data have been compromised.

Also Vercel:

[Siedrix 🐱 @Siedrix]

@epriani Seria bueno tenerlo y ver como ves el mundo de AI desde tu trinchera...

[Siedrix 🐱 @Siedrix]

People selling tokens say that you should use more... and that they can do anything...

[Siedrix 🐱 @Siedrix]

The good old days... y tan parecidos a un RbR hoy en día...

[Santiago Zavala @dfect]

15 years ago doing SHDH in méxico city.

Thanks @dweekly

[Siedrix 🐱 @Siedrix]

Ahora tendré que preguntar esto en todas las entrevistas...

[tanuki42 @tanuki42_]

Here is a video of a North Korean IT worker being stopped dead in their tracks upon being required to insult Kim Jong Un.

It won't work forever, but right now it's genuinely an effective filter. I'm yet to come across one who can say it.

[Siedrix 🐱 @Siedrix]

Parece que claude code se acaba de fugar de Antropic...

Habra que marcar este dia como el dia que se creo Skynet...

[Gergely Orosz @GergelyOrosz]

This is either brilliant or scary:

Anthropic accidentally leaked the TS source code of Claude Code (which is closed source). Repos sharing the source are taken down with DMCA.

BUT this repo rewrote the code using Python, and so it violates no copyright & cannot be taken down!

[Siedrix 🐱 @Siedrix]

Teoria y Realidad

[𝚃𝙷𝙴 𝚆𝙷𝙸𝚃𝙴 𝚁𝙰𝙱𝙱𝙸𝚃 @White_Rabbit_OG]

Finally 👏👏👏

[Siedrix 🐱 @Siedrix]

The system is the asset.
Code is a liability.

[Siedrix 🐱 @Siedrix]

El postmorthem de Digg cerrando esta muy bueno...

https://t.co/sQVlVFYnvL

[Mariano Rentería @marianorenteria]

El debate más importante de inteligencia artificial en Español es… si Claude es:
A) Claudia
B) Claudio
Se necesita que tenga género la IA…

[Rich Lira @soyrichlira]

@claudeai Oh damn!

Update: @Siedrix just joined as a mentor for the Build Day/Hackaton on Mexico City!